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Journal Articles
- 2022
[j2]Kyle Luther, H. Sebastian Seung:
Sensitivity of Sparse Codes to Image Distortions. Neural Comput. 34(7): 1616-1635 (2022)- 2021
- [j1]Kisuk Lee
, Ran Lu, Kyle Luther, H. Sebastian Seung:
Learning and Segmenting Dense Voxel Embeddings for 3D Neuron Reconstruction. IEEE Trans. Medical Imaging 40(12): 3801-3811 (2021)
Conference and Workshop Papers
- 2022
- [c3]Kyle Luther, H. Sebastian Seung:
Kernel similarity matching with Hebbian networks. NeurIPS 2022 - 2019
- [c2]Kyle L. Luther, Runzhe Yang, H. Sebastian Seung:
Unsupervised learning by a "softened" correlation game: duality and convergence. ACSSC 2019: 876-883 - [c1]Kyle Luther, H. Sebastian Seung:
Learning Metric Graphs for Neuron Segmentation in Electron Microscopy Images. ISBI 2019: 244-248
Informal and Other Publications
- 2023
- [i8]Kyle L. Luther, H. Sebastian Seung:
Stretched sinograms for limited-angle tomographic reconstruction with neural networks. CoRR abs/2306.10201 (2023) - [i7]Kyle Luther, H. Sebastian Seung:
DDGM: Solving inverse problems by Diffusive Denoising of Gradient-based Minimization. CoRR abs/2307.04946 (2023) - 2022
- [i6]Kyle Luther, H. Sebastian Seung:
Sensitivity of sparse codes to image distortions. CoRR abs/2204.07466 (2022) - [i5]Kyle Luther, H. Sebastian Seung:
Kernel similarity matching with Hebbian neural networks. CoRR abs/2204.07475 (2022) - [i4]Kyle Luther, H. Sebastian Seung:
Stacked unsupervised learning with a network architecture found by supervised meta-learning. CoRR abs/2206.02716 (2022) - 2019
- [i3]Kyle Luther, H. Sebastian Seung:
Learning Metric Graphs for Neuron Segmentation In Electron Microscopy Images. CoRR abs/1902.00100 (2019) - [i2]Kyle Luther, H. Sebastian Seung:
Variance-Preserving Initialization Schemes Improve Deep Network Training: But Which Variance is Preserved? CoRR abs/1902.04942 (2019) - [i1]Kisuk Lee, Ran Lu, Kyle Luther, H. Sebastian Seung:
Learning Dense Voxel Embeddings for 3D Neuron Reconstruction. CoRR abs/1909.09872 (2019)
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